Plasma Metabolites Link Dietary Patterns to Stroke Risk
Zsuzsanna Ament PhD
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Search for more papers by this authorAmit Patki MS
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorYan Gao MPH
The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MA, USA
Search for more papers by this authorNaruchorn Kijpaisalratana MD, PhD
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Division of Neurology, Department of Medicine and Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
Search for more papers by this authorBoyi Guo MS
Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorNinad S. Chaudhary PhD
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
The University of Texas Health Science Center at Houston, Houston, TX, USA
Search for more papers by this authorAna-Lucia Garcia Guarniz MD
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Search for more papers by this authorRobert Gerszten MD
Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
Search for more papers by this authorAdolfo Correa MD, PhD
The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MA, USA
Search for more papers by this authorMary Cushman MD, MS
Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
Search for more papers by this authorSuzanne Judd PhD
Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorM. Ryan Irvin PhD
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorCorresponding Author
W. Taylor Kimberly MD, PhD
Harvard Medical School, Boston, MA, USA
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Address correspondence to Kimberly, Harvard Medical School, 55 Fruit Street, Lunder 644, Boston, Massachusetts, 02114, USA. E-mail: [email protected]
Search for more papers by this authorZsuzsanna Ament PhD
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Search for more papers by this authorAmit Patki MS
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorYan Gao MPH
The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MA, USA
Search for more papers by this authorNaruchorn Kijpaisalratana MD, PhD
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Division of Neurology, Department of Medicine and Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
Search for more papers by this authorBoyi Guo MS
Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorNinad S. Chaudhary PhD
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
The University of Texas Health Science Center at Houston, Houston, TX, USA
Search for more papers by this authorAna-Lucia Garcia Guarniz MD
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Search for more papers by this authorRobert Gerszten MD
Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
Search for more papers by this authorAdolfo Correa MD, PhD
The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MA, USA
Search for more papers by this authorMary Cushman MD, MS
Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, VT, USA
Search for more papers by this authorSuzanne Judd PhD
Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorM. Ryan Irvin PhD
Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
Search for more papers by this authorCorresponding Author
W. Taylor Kimberly MD, PhD
Harvard Medical School, Boston, MA, USA
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
Address correspondence to Kimberly, Harvard Medical School, 55 Fruit Street, Lunder 644, Boston, Massachusetts, 02114, USA. E-mail: [email protected]
Search for more papers by this authorAbstract
Objective
While dietary intake is linked to stroke risk, surrogate markers that could inform personalized dietary interventions are lacking. We identified metabolites associated with diet patterns and incident stroke in a nested cohort from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study.
Methods
Levels of 162 metabolites were measured in baseline plasma from stroke cases (n = 1,198) and random controls (n = 904). We examined associations between metabolites and a plant-based diet pattern previously linked to reduced stroke risk in REGARDS. Secondary analyses included 3 additional stroke-associated diet patterns: a Mediterranean, Dietary Approaches to Stop Hypertension (DASH), and Southern diet. Metabolites were tested using Cox proportional hazards models with incident stroke as the outcome. Replication was performed in the Jackson Heart Study (JHS). Inverse odds ratio-weighted mediation was used to determine whether metabolites mediated the association between a plant-based diet and stroke risk.
Results
Metabolites associated with a plant-based diet included the gut metabolite indole-3-propionic acid (β = 0.23, 95% confidence interval [CI] [0.14, 0.33], p = 1.14 × 10−6), guanosine (β = −0.13, 95% CI [−0.19, −0.07], p = 6.48 × 10−5), gluconic acid (β = −0.11, 95% CI [−0.18, −0.04], p = 2.06 × 10−3), and C7 carnitine (β = −0.16, 95% CI [−0.24, −0.09], p = 4.14 × 10−5). All of these metabolites were associated with both additional diet patterns and altered stroke risk. Mediation analyses identified guanosine (32.6% mediation, p = 1.51 × 10−3), gluconic acid (35.7%, p = 2.28 × 10−3), and C7 carnitine (26.2%, p = 1.88 × 10−2) as mediators linking a plant-based diet to reduced stroke risk.
Interpretation
A subset of diet-related metabolites are associated with risk of stroke. These metabolites could serve as surrogate markers that inform dietary interventions. ANN NEUROL 2023;93:500–510
Potential Conflicts of Interest
Nothing to report.
Supporting Information
| Filename | Description |
|---|---|
| ana26552-sup-0001-TableS1.docxWord 2007 document , 203.1 KB | Table S1. All associations between 162 metabolites and the plant-based, Southern, Mediterranean, and Dietary Approaches to Stop Hypertension (DASH) diet patterns. Weighted linear regressions were adjusted for age, race, sex, and time to measurement (see Methods). |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
References
- 1He FJ, Nowson CA, MacGregor GA. Fruit and vegetable consumption and stroke: meta-analysis of cohort studies. Lancet 2006; 367: 320–326.
- 2Judd SE, Gutiérrez OM, Newby PK, et al. Dietary patterns are associated with incident stroke and contribute to excess risk of stroke in Black Americans. Stroke 2013; 44: 3305–3311.
- 3Chiavaroli L, Viguiliouk E, Nishi S, et al. DASH dietary pattern and cardiometabolic outcomes: an umbrella review of systematic reviews and meta-analyses. Nutrients 2019; 11: 338. https://doi.org/10.3390/nu11020338.
- 4Tsivgoulis G, Psaltopoulou T, Wadley VG, et al. Adherence to a Mediterranean diet and prediction of incident stroke. Stroke 2015; 46: 780–785.
- 5Kleindorfer DO, Towfighi A, Chaturvedi S, et al. 2021 Guideline for the prevention of stroke in patients with stroke and transient ischemic attack: A guideline from the American Heart Association/American Stroke Association. Stroke 2021; 52: e364–e467.
- 6Singh RK, Chang HW, Yan D, et al. Influence of diet on the gut microbiome and implications for human health. J Transl Med 2017; 15: 73. https://doi.org/10.1186/s12967-017-1175-y.
- 7Rothschild D, Weissbrod O, Barkan E, et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 2018; 555: 210–215.
- 8Zmora N, Suez J, Elinav E. You are what you eat: diet, health and the gut microbiota. Nat Rev Gastroenterol Hepatol 2019; 16: 35–56.
- 9Valdes AM, Walter J, Segal E, Spector TD. Role of the gut microbiota in nutrition and health. BMJ 2018; 361: k2179. https://doi.org/10.1136/bmj.k2179.
- 10Rooks MG, Garrett WS. Gut microbiota, metabolites and host immunity. Nat Rev Immunol 2016; 16: 341–352.
- 11Witkowski M, Weeks TL, Hazen SL. Gut microbiota and cardiovascular disease. Circ Res 2020; 127: 553–570.
- 12Vogt NM, Kerby RL, Dill-McFarland KA, et al. Gut microbiome alterations in Alzheimer's disease. Sci Rep 2017; 7: 13537. https://doi.org/10.1038/s41598-017-13601-y.
- 13Howard VJ, Cushman M, Pulley L, et al. The Reasons for Geographic and Racial Differences in Stroke study: objectives and design. Neuroepidemiology 2005; 25: 135–143.
- 14Ament Z, Patki A, Chaudhary N, et al. Nucleosides associated with incident ischemic stroke in the REGARDS and JHS cohorts. Neurology 2022; 98: e2097–e2107.
- 15Guasch-Ferré M, Bhupathiraju SN, Hu FB. Use of metabolomics in improving assessment of dietary intake. Clin Chem 2018; 64: 82–98.
- 16Rebholz CM, Gao Y, Talegawkar S, et al. Metabolomic markers of Southern dietary patterns in the Jackson Heart Study. Mol Nutr Food Res 2021; 65:e2000796. https://doi.org/10.1002/mnfr.202000796.
- 17Montaner J, Ramiro L, Simats A, et al. Multilevel omics for the discovery of biomarkers and therapeutic targets for stroke. Nat Rev Neurol 2020; 16: 247–264.
- 18Howard VJ, Kleindorfer DO, Judd SE, et al. Disparities in stroke incidence contributing to disparities in stroke mortality. Ann Neurol 2011; 69: 619–627.
- 19Gillett SR, Boyle RH, Zakai NA, et al. Validating laboratory results in a national observational cohort study without field centers: the Reasons for Geographic and Racial Differences in Stroke cohort. Clin Biochem 2014; 47: 243–246.
- 20Lefkowitz DS, Brust JCM, Goldman L, et al. A pilot study of the end point verification system in the Asymptomatic Carotid Atherosclerosis Study. J Stroke Cerebrovasc Dis 1992; 2: 92–99.
- 21Spence JD, Howard VJ, Chambless LE, et al. Vitamin Intervention for Stroke Prevention (VISP) trial: rationale and design. Neuroepidemiology 2001; 20: 16–25.
- 22Chambless LE, Toole JF, Nieto FJ, et al. Association between symptoms reported in a population questionnaire and future ischemic stroke: the ARIC study. Neuroepidemiology 2004; 23: 33–37.
- 23Cushman M, Judd SE, Howard VJ, et al. N-terminal pro–B-type natriuretic peptide and stroke risk. Stroke 2014; 45: 1646–1650.
- 24Zakai NA, Judd SE, Alexander K, et al. ABO blood type and stroke risk: the REasons for Geographic And Racial Differences in Stroke study. J Thromb Haemost 2014; 12: 564–570.
- 25Olson NC, Cushman M, Judd SE, et al. Associations of coagulation factors IX and XI levels with incident coronary heart disease and ischemic stroke: the REGARDS study. J Thromb Haemost 2017; 15: 1086–1094.
- 26Chaudhary NS, Bridges SL, Saag KG, et al. Severity of hypertension mediates the association of hyperuricemia with stroke in the REGARDS case cohort study. Hypertension 2020; 75: 246–256.
- 27Ament Z, Bevers MB, Wolcott Z, et al. Uric acid and gluconic acid as predictors of hyperglycemia and cytotoxic injury after stroke. Transl Stroke Res 2021; 12: 293–302.
- 28Stapleton CJ, Acharjee A, Irvine HJ, et al. High-throughput metabolite profiling: identification of plasma taurine as a potential biomarker of functional outcome after aneurysmal subarachnoid hemorrhage. J Neurosurg 2020; 133: 1842–1849.
- 29Kimberly WT, O'Sullivan JF, Nath AK, et al. Metabolite profiling identifies anandamide as a biomarker of nonalcoholic steatohepatitis. JCI Insight 2017; 2:e92989. https://doi.org/10.1172/jci.insight.92989.
- 30Nelson SE, Ament Z, Wolcott Z, et al. Succinate links atrial dysfunction and cardioembolic stroke. Neurology 2019; 92: e802–e810.
- 31Judd SE, Letter AJ, Shikany JM, et al. Dietary patterns derived using exploratory and confirmatory factor analysis are stable and generalizable across race, region, and gender subgroups in the REGARDS study. Front Nutr 2015. https://doi.org/10.3389/fnut.2014.00029.
- 32Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med 2003; 348: 2599–2608.
- 33Fung TT, Chiuve SE, McCullough ML, et al. Adherence to a DASH-style diet and risk of coronary heart disease and stroke in women. Arch Intern Med 2008; 168: 713–720.
- 34Stevens VL, Hoover E, Wang Y, Zanetti KA. Pre-analytical factors that affect metabolite stability in human urine, plasma, and serum: a review. Metabolites 2019; 9: 156. https://doi.org/10.3390/metabo9080156.
- 35Goyal P, Balkan L, Ringel JB, et al. The Dietary Approaches to Stop Hypertension (DASH) diet pattern and incident heart failure. J Card Fail 2021; 27: 512–521.
- 36Shikany JM, Safford MM, Newby PK, et al. Southern dietary pattern is associated with hazard of acute coronary heart disease in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. Circulation 2015; 132: 804–814.
- 37Nguyen QC, Osypuk TL, Schmidt NM, et al. Practical guidance for conducting mediation analysis with multiple mediators using inverse odds ratio weighting. Am J Epidemiol 2015; 181: 349–356.
- 38Tahir UA, Katz DH, Zhao T, et al. Metabolomic profiles and heart failure risk in Black adults: insights from the Jackson Heart Study. Circ Heart Fail 2021; 14:e007275. https://doi.org/10.1161/CIRCHEARTFAILURE.120.007275.
- 39Cruz DE, Tahir UA, Hu J, et al. Metabolomic analysis of coronary heart disease in an African American cohort from the Jackson Heart Study. JAMA Cardiol 2022; 7: 184–194.
- 40Larsson SC, Wallin A, Wolk A. Dietary Approaches to Stop Hypertension Diet and incidence of stroke. Stroke 2016; 47: 986–990.
- 41Louca P, Nogal A, Mompeo O, et al. Body mass index mediates the effect of the DASH diet on hypertension: common metabolites underlying the association. J Hum Nutr Diet 2022; 35: 214–222.
- 42Li J, Guasch-Ferré M, Chung W, et al. The Mediterranean diet, plasma metabolome, and cardiovascular disease risk. Eur Heart J 2020; 41: 2645–2656.
- 43Agus A, Planchais J, Sokol H. Gut microbiota regulation of tryptophan metabolism in health and disease. Cell Host Microbe 2018; 23: 716–724.
- 44Konopelski P, Mogilnicka I. Biological effects of indole-3-propionic acid, a gut microbiota-derived metabolite, and its precursor tryptophan in mammals' health and disease. Int J Mol Sci 2022; 23:1222. https://doi.org/10.3390/ijms23031222.
- 45Sauer N, Mosenthin R, Bauer E. The role of dietary nucleotides in single-stomached animals. Nutr Res Rev 2011; 24: 46–59.
- 46Han Z, Wyche JH. Guanosine induces necrosis of cultured aortic endothelial cells. Am J Pathol 1994; 145: 423–427.
- 47Tsukahara T, Koyama H, Okada M, Ushida K. Stimulation of butyrate production by gluconic acid in batch culture of pig cecal digesta and identification of butyrate-producing bacteria. J Nutr 2002; 132: 2229–2234.
- 48Flanagan JL, Simmons PA, Vehige J, et al. Role of carnitine in disease. Nutr Metab 2010; 7: 30. https://doi.org/10.1186/1743-7075-7-30.
- 49Subar AF, Freedman LS, Tooze JA, et al. Addressing current criticism regarding the value of self-report dietary data. J Nutr 2015; 145: 2639–2645.
- 50Rafiq T, Azab SM, Teo KK, et al. Nutritional metabolomics and the classification of dietary biomarker candidates: a critical review. Adv Nutr 2021; 12: 2333–2357.
Citing Literature
